Objective: To analyze the relationship between parental psychological control and Internet Gaming Disorder (IGD) among junior high school students, so as to provide evidence for preventing IGD development in adolescents. Methods: From August 2019 to February 2020, a survey was conducted among 1 169 junior high school students from three middle schools in Xian using stratified cluster sampling. The Parental Psychological Control Scale and IGD Scale were administered to assess parental psychological control and IGD prevalence. Univariate and binary Logistic regression analyses were used to explore IGD risk factors and their correlation with parental psychological control. Results: The detection rate of IGD in middle school students was 19.9%(184/1 169). Multivariate Logistic regression revealed that compared to those with lower parental psychological control scores(≤21 points), students with higher parental psychological control scores (>21 points) had a higher risk of IGD (OR=1.82, 95%CI=1.21-2.74), a 1.58fold higher risk of selfperceived gaming addiction (95%CI=1.07-2.30), as well as reduced likelihood of seeking external help to reduce gaming time (OR=0.66, 95%CI=0.47-0.94) (P<0.05). Conclusions Parental psychological control may elevate the risks of IGD and selfperceived addiction while diminishing proactive helpseeking behaviors to reduce gaming time. Parents should enhance communication with adolescents and provide positive guidance to mitigate potential gamingrelated harms.

Objective: To explore glymphatic impairment in pediatric refractory epilepsy (RE) using multi-parameter magnetic resonance imaging (MRI), assess its relationship with white-matter (WM) abnormalities and clinical indicators, and preliminarily evaluate the performance of multi-parameter MRI in discriminating RE from drug-sensitive epilepsy (DSE). Materials and Methods: We retrospectively included 70 patients with DSE (mean age, 9.7 ± 3.5 years; male:female, 37:33) and 26 patients with RE (9.0 ± 2.9 years; male:female, 12:14). The diffusion tensor imaging analysis along the perivascular space (DTI-ALPS) index as well as fractional anisotropy (FA), mean diffusivity (MD), and nodal efficiency values were measured and compared between patients with RE and DSE. With sex and age as covariables, differences in the FA and MD values were analyzed using tract-based spatial statistics, and nodal efficiency was analyzed using a linear model. Pearson’s partial correlation was analyzed. Receiver operating characteristic (ROC) curves were used to evaluate the discrimination performance of the MRI-based machine-learning models through five-fold cross-validation. Results: In the RE group, FA decreased and MD increased in comparison with the corresponding values in the DSE group, and these differences mainly involved the callosum, right and left corona radiata, inferior and superior longitudinal fasciculus, and posterior thalamic radiation (threshold-free cluster enhancement, P < 0.05). The RE group also showed reduced nodal efficiency, which mainly involved the limbic system, default mode network, and visual network (false discovery rate, P < 0.05), and significantly lower DTI-ALPS index (F = 2.0, P = 0.049). The DTI-ALPS index was positively correlated with FA (0.25 ≤ r ≤ 0.32) and nodal efficiency (0.22 ≤ r ≤ 0.37), and was negatively correlated with the MD (-0.24 ≤ r≤ -0.34) and seizure frequency (r = -0.47). A machine-learning model combining DTI-ALPS, FA, MD, and nodal efficiency achieved a cross-validated ROC curve area of 0.83 (sensitivity, 78.2%; specificity, 84.8%). Conclusion Pediatric patients with RE showed impaired glymphatic function in comparison with patients with DSE, which was correlated with WM abnormalities and seizure frequency. Multi-parameter MRI may be feasible for distinguishing RE from DSE.

Objective: To explore glymphatic impairment in pediatric refractory epilepsy (RE) using multi-parameter magnetic resonance imaging (MRI), assess its relationship with white-matter (WM) abnormalities and clinical indicators, and preliminarily evaluate the performance of multi-parameter MRI in discriminating RE from drug-sensitive epilepsy (DSE). Materials and Methods: We retrospectively included 70 patients with DSE (mean age, 9.7 ± 3.5 years; male:female, 37:33) and 26 patients with RE (9.0 ± 2.9 years; male:female, 12:14). The diffusion tensor imaging analysis along the perivascular space (DTI-ALPS) index as well as fractional anisotropy (FA), mean diffusivity (MD), and nodal efficiency values were measured and compared between patients with RE and DSE. With sex and age as covariables, differences in the FA and MD values were analyzed using tract-based spatial statistics, and nodal efficiency was analyzed using a linear model. Pearson’s partial correlation was analyzed. Receiver operating characteristic (ROC) curves were used to evaluate the discrimination performance of the MRI-based machine-learning models through five-fold cross-validation. Results: In the RE group, FA decreased and MD increased in comparison with the corresponding values in the DSE group, and these differences mainly involved the callosum, right and left corona radiata, inferior and superior longitudinal fasciculus, and posterior thalamic radiation (threshold-free cluster enhancement, P < 0.05). The RE group also showed reduced nodal efficiency, which mainly involved the limbic system, default mode network, and visual network (false discovery rate, P < 0.05), and significantly lower DTI-ALPS index (F = 2.0, P = 0.049). The DTI-ALPS index was positively correlated with FA (0.25 ≤ r ≤ 0.32) and nodal efficiency (0.22 ≤ r ≤ 0.37), and was negatively correlated with the MD (-0.24 ≤ r≤ -0.34) and seizure frequency (r = -0.47). A machine-learning model combining DTI-ALPS, FA, MD, and nodal efficiency achieved a cross-validated ROC curve area of 0.83 (sensitivity, 78.2%; specificity, 84.8%). Conclusion Pediatric patients with RE showed impaired glymphatic function in comparison with patients with DSE, which was correlated with WM abnormalities and seizure frequency. Multi-parameter MRI may be feasible for distinguishing RE from DSE.

Objective: To explore glymphatic impairment in pediatric refractory epilepsy (RE) using multi-parameter magnetic resonance imaging (MRI), assess its relationship with white-matter (WM) abnormalities and clinical indicators, and preliminarily evaluate the performance of multi-parameter MRI in discriminating RE from drug-sensitive epilepsy (DSE). Materials and Methods: We retrospectively included 70 patients with DSE (mean age, 9.7 ± 3.5 years; male:female, 37:33) and 26 patients with RE (9.0 ± 2.9 years; male:female, 12:14). The diffusion tensor imaging analysis along the perivascular space (DTI-ALPS) index as well as fractional anisotropy (FA), mean diffusivity (MD), and nodal efficiency values were measured and compared between patients with RE and DSE. With sex and age as covariables, differences in the FA and MD values were analyzed using tract-based spatial statistics, and nodal efficiency was analyzed using a linear model. Pearson’s partial correlation was analyzed. Receiver operating characteristic (ROC) curves were used to evaluate the discrimination performance of the MRI-based machine-learning models through five-fold cross-validation. Results: In the RE group, FA decreased and MD increased in comparison with the corresponding values in the DSE group, and these differences mainly involved the callosum, right and left corona radiata, inferior and superior longitudinal fasciculus, and posterior thalamic radiation (threshold-free cluster enhancement, P < 0.05). The RE group also showed reduced nodal efficiency, which mainly involved the limbic system, default mode network, and visual network (false discovery rate, P < 0.05), and significantly lower DTI-ALPS index (F = 2.0, P = 0.049). The DTI-ALPS index was positively correlated with FA (0.25 ≤ r ≤ 0.32) and nodal efficiency (0.22 ≤ r ≤ 0.37), and was negatively correlated with the MD (-0.24 ≤ r≤ -0.34) and seizure frequency (r = -0.47). A machine-learning model combining DTI-ALPS, FA, MD, and nodal efficiency achieved a cross-validated ROC curve area of 0.83 (sensitivity, 78.2%; specificity, 84.8%). Conclusion Pediatric patients with RE showed impaired glymphatic function in comparison with patients with DSE, which was correlated with WM abnormalities and seizure frequency. Multi-parameter MRI may be feasible for distinguishing RE from DSE.

Objective: To explore glymphatic impairment in pediatric refractory epilepsy (RE) using multi-parameter magnetic resonance imaging (MRI), assess its relationship with white-matter (WM) abnormalities and clinical indicators, and preliminarily evaluate the performance of multi-parameter MRI in discriminating RE from drug-sensitive epilepsy (DSE). Materials and Methods: We retrospectively included 70 patients with DSE (mean age, 9.7 ± 3.5 years; male:female, 37:33) and 26 patients with RE (9.0 ± 2.9 years; male:female, 12:14). The diffusion tensor imaging analysis along the perivascular space (DTI-ALPS) index as well as fractional anisotropy (FA), mean diffusivity (MD), and nodal efficiency values were measured and compared between patients with RE and DSE. With sex and age as covariables, differences in the FA and MD values were analyzed using tract-based spatial statistics, and nodal efficiency was analyzed using a linear model. Pearson’s partial correlation was analyzed. Receiver operating characteristic (ROC) curves were used to evaluate the discrimination performance of the MRI-based machine-learning models through five-fold cross-validation. Results: In the RE group, FA decreased and MD increased in comparison with the corresponding values in the DSE group, and these differences mainly involved the callosum, right and left corona radiata, inferior and superior longitudinal fasciculus, and posterior thalamic radiation (threshold-free cluster enhancement, P < 0.05). The RE group also showed reduced nodal efficiency, which mainly involved the limbic system, default mode network, and visual network (false discovery rate, P < 0.05), and significantly lower DTI-ALPS index (F = 2.0, P = 0.049). The DTI-ALPS index was positively correlated with FA (0.25 ≤ r ≤ 0.32) and nodal efficiency (0.22 ≤ r ≤ 0.37), and was negatively correlated with the MD (-0.24 ≤ r≤ -0.34) and seizure frequency (r = -0.47). A machine-learning model combining DTI-ALPS, FA, MD, and nodal efficiency achieved a cross-validated ROC curve area of 0.83 (sensitivity, 78.2%; specificity, 84.8%). Conclusion Pediatric patients with RE showed impaired glymphatic function in comparison with patients with DSE, which was correlated with WM abnormalities and seizure frequency. Multi-parameter MRI may be feasible for distinguishing RE from DSE.

Objective: To explore glymphatic impairment in pediatric refractory epilepsy (RE) using multi-parameter magnetic resonance imaging (MRI), assess its relationship with white-matter (WM) abnormalities and clinical indicators, and preliminarily evaluate the performance of multi-parameter MRI in discriminating RE from drug-sensitive epilepsy (DSE). Materials and Methods: We retrospectively included 70 patients with DSE (mean age, 9.7 ± 3.5 years; male:female, 37:33) and 26 patients with RE (9.0 ± 2.9 years; male:female, 12:14). The diffusion tensor imaging analysis along the perivascular space (DTI-ALPS) index as well as fractional anisotropy (FA), mean diffusivity (MD), and nodal efficiency values were measured and compared between patients with RE and DSE. With sex and age as covariables, differences in the FA and MD values were analyzed using tract-based spatial statistics, and nodal efficiency was analyzed using a linear model. Pearson’s partial correlation was analyzed. Receiver operating characteristic (ROC) curves were used to evaluate the discrimination performance of the MRI-based machine-learning models through five-fold cross-validation. Results: In the RE group, FA decreased and MD increased in comparison with the corresponding values in the DSE group, and these differences mainly involved the callosum, right and left corona radiata, inferior and superior longitudinal fasciculus, and posterior thalamic radiation (threshold-free cluster enhancement, P < 0.05). The RE group also showed reduced nodal efficiency, which mainly involved the limbic system, default mode network, and visual network (false discovery rate, P < 0.05), and significantly lower DTI-ALPS index (F = 2.0, P = 0.049). The DTI-ALPS index was positively correlated with FA (0.25 ≤ r ≤ 0.32) and nodal efficiency (0.22 ≤ r ≤ 0.37), and was negatively correlated with the MD (-0.24 ≤ r≤ -0.34) and seizure frequency (r = -0.47). A machine-learning model combining DTI-ALPS, FA, MD, and nodal efficiency achieved a cross-validated ROC curve area of 0.83 (sensitivity, 78.2%; specificity, 84.8%). Conclusion Pediatric patients with RE showed impaired glymphatic function in comparison with patients with DSE, which was correlated with WM abnormalities and seizure frequency. Multi-parameter MRI may be feasible for distinguishing RE from DSE.

ObjectiveTo explore the mechanism of Huanglian Wendantang on damp-heat type diabetes enteropathy rats based on the G protein coupled bile acid receptor 5/glucagon like peptide-1 （TGR5/GLP-1） signaling pathway and intestinal flora. MethodsA total of 72 male Sprague Dawley （SD） rats were adaptively fed for one week. Twelve SD rats were randomly selected as a blank group and fed with an ordinary diet. The rest of the SD rats were fasted for 12 hours without water. A rat model with damp-heat type diabetes enteropathy was made by left intraperitoneal injection of streptozotocin （55 mg·kg^-1） and high sugar and high fat diet （20% sucrose solution + high fat diet） in a humid and hot environment （artificial climate box： temperature 30-34 ℃， relative humidity： 85%-95%）. After successful modeling， the rats were randomly divided into a model group， a metformin group （200 mg·kg^-1）， low-dose， medium-dose， and high-dose Huanglian Wendantang groups （7.10， 14.20， 28.39 g·kg^-1）， with 12 rats in each group. The normal group and the model group were orally administered with physiological saline once a day for 6 consecutive weeks. During the observation period， the weight and blood glucose levels of rats were measured and recorded weekly. After the administration， fresh feces were collected from rats， and 16S rRNA sequencing technology was used to study the differences and changes in intestinal flora among different groups. The levels of tumor necrosis factor-α （TNF-α） and interleukin-6 （IL-6） in the serum of rats were detected by enzyme-linked immunosorbent assay （ELISA）， and the pathological morphological changes of colon tissue were examined. The expression of TGR5 and GLP-1 in colon tissue was detected by immunohistochemistry， and the expression of TGR5 and GLP-1 proteins in colon tissue was measured by Western blot. ResultsCompared with the blank group， the model group showed a decrease in body weight， an increase in blood glucose， and significant damp-heat symptoms. The levels of IL-6 and TNF-α in serum were significantly increased （P<0.01）. The expression of TGR5 and GLP-1 was decreased （P<0.01）， and the pathogenic bacteria were increased. Compared with the model group， the treatment groups exhibited improvements in body weight， blood glucose levels， and damp-heat syndrome in rats. Among them， the high-dose group of Huanglian Wendantang displayed the most significant improvement effect， with significantly reduced inflammation levels （P<0.01） and elevated expression of TGR5 and GLP-1 （P<0.01）. Colonic pathological sections showed that Huanglian Wendantang could effectively ameliorate colonic pathological changes. The 16S rRNA sequencing result indicated a significant increase in beneficial bacteria in the treatment groups. ConclusionHuanglian Wendantang can effectively ameliorate the damp-heat symptoms and blood glucose levels in rats with damp-heat type diabetes enteropathy， and it may exert an effect by regulating the TGR5/GLP-1 signaling pathway and intestinal flora disorder.

ObjectivePrimary liver cancer, predominantly hepatocellular carcinoma (HCC), is a significant global health issue, ranking as the sixth most diagnosed cancer and the third leading cause of cancer-related mortality. Accurate and early diagnosis of HCC is crucial for effective treatment, as HCC and non-HCC malignancies like intrahepatic cholangiocarcinoma (ICC) exhibit different prognoses and treatment responses. Traditional diagnostic methods, including liver biopsy and contrast-enhanced ultrasound (CEUS), face limitations in applicability and objectivity. The primary objective of this study was to develop an advanced, light-weighted classification network capable of distinguishing HCC from other non-HCC malignancies by leveraging the automatic analysis of brightness changes in CEUS images. The ultimate goal was to create a user-friendly and cost-efficient computer-aided diagnostic tool that could assist radiologists in making more accurate and efficient clinical decisions. MethodsThis retrospective study encompassed a total of 161 patients, comprising 131 diagnosed with HCC and 30 with non-HCC malignancies. To achieve accurate tumor detection, the YOLOX network was employed to identify the region of interest (ROI) on both B-mode ultrasound and CEUS images. A custom-developed algorithm was then utilized to extract brightness change curves from the tumor and adjacent liver parenchyma regions within the CEUS images. These curves provided critical data for the subsequent analysis and classification process. To analyze the extracted brightness change curves and classify the malignancies, we developed and compared several models. These included one-dimensional convolutional neural networks (1D-ResNet, 1D-ConvNeXt, and 1D-CNN), as well as traditional machine-learning methods such as support vector machine (SVM), ensemble learning (EL), k-nearest neighbor (KNN), and decision tree (DT). The diagnostic performance of each method in distinguishing HCC from non-HCC malignancies was rigorously evaluated using four key metrics: area under the receiver operating characteristic (AUC), accuracy (ACC), sensitivity (SE), and specificity (SP). ResultsThe evaluation of the machine-learning methods revealed AUC values of 0.70 for SVM, 0.56 for ensemble learning, 0.63 for KNN, and 0.72 for the decision tree. These results indicated moderate to fair performance in classifying the malignancies based on the brightness change curves. In contrast, the deep learning models demonstrated significantly higher AUCs, with 1D-ResNet achieving an AUC of 0.72, 1D-ConvNeXt reaching 0.82, and 1D-CNN obtaining the highest AUC of 0.84. Moreover, under the five-fold cross-validation scheme, the 1D-CNN model outperformed other models in both accuracy and specificity. Specifically, it achieved accuracy improvements of 3.8% to 10.0% and specificity enhancements of 6.6% to 43.3% over competing approaches. The superior performance of the 1D-CNN model highlighted its potential as a powerful tool for accurate classification. ConclusionThe 1D-CNN model proved to be the most effective in differentiating HCC from non-HCC malignancies, surpassing both traditional machine-learning methods and other deep learning models. This study successfully developed a user-friendly and cost-efficient computer-aided diagnostic solution that would significantly enhances radiologists’ diagnostic capabilities. By improving the accuracy and efficiency of clinical decision-making, this tool has the potential to positively impact patient care and outcomes. Future work may focus on further refining the model and exploring its integration with multimodal ultrasound data to maximize its accuracy and applicability.

Objective To observe clinical outcomes of propofol and remazolam in patients undergoing elective painless fiberoptic bronchoscopic biopsy.Methods Patients who underwent painless fibreoptic bronchoscopic biopsy in our hospital from March 2022 to April 2023 were selected for the study and divided into 2 groups using simple randomisation method.In the control group,anaesthesia was induced with 1 mg·kg-1 propofol,3 μg·kg-1 fentanyl,0.1 mg·kg-1 cis-atracurium,and anaesthesia was maintained with 4-6 mg·kg-1·h-1 propofol.In the treatment group,anaesthesia was induced with 0.2 mg·kg-1 remazolam,3 μg·kg-1 fentanyl,0.1 mg·kg-1 cis-atracurium,and anaesthesia was maintained with 0.2-0.4 mg·kg-1·h-1 remazolam.We compared the awakening time,laryngeal mask removal time,microscopy time,and the proportion of additional anaesthetics in the 2 groups,and detected the levels of S100β,neuron-specific enolase(NSE),interleukin-6(IL-6),tumour necrosis factor-alpha(TNF-α)in the 2 groups preoperatively and at 24 h postoperatively,and statistically counted the occurrences of adverse reactions in the 2 groups.Results The time for pulling out the laryngeal mask in the treatment group was significantly lower than that in the control group,while the time for microscopy,time for awakening,and proportion of additional anaesthesia drugs were not statistically significant when compared with that in the control group(all P＞0.05).The overall anaesthesia effect grading of the test group was not statistically significant when compared with the control group(P＞0.05).S100β were(0.66±0.17)and(0.78±0.21)μg·L-1;NSE were(8.47±1.78)and(11.47±2.06)μg·L-1;IL-6 were(8.64±1.21)and(12.89±1.47)pg·mL-1;TNF-α were(6.27±1.07)and(9.13±1.41)pg·mL-1,respectively,which were higher than that of preoperative period,and the treatment group was lower than that of the control group at 24 h postoperatively,and the difference was statistically significant(all P＜0.05).The incidence of adverse drug reactions in the treatment group and the control group were 13.75％and 22.50％,respectively,and the difference was not statistically significant(P＞0.05).Conclusion The use of remazolam in painless fiberoptic bronchoscopic biopsy is less neurologically damaging,stabilizes hemodynamics.

Objective We aimed to investigate(i)the preventive and therapeutic effects of Huogu Muli Prescription(HGMLP),a Chinese medical compound consisting of epimedii folium,drynariae rhizoma,and ostreae concha,on postmenopausal osteoporosis(PMOP)rats and(ii)whether it exerts its effects by regulating the osteoclast-osteogenesis balance.Methods Forty-eight female Sprague-Dawley rats were randomly divided into the following six groups:(i)the sham-operated group,(ii)the model group,(iii)the Qianggu Capsule group,(iv)the calcium carbonate group,and(v,vi)the HGMLP low-dose and high-dose groups(n = 8 rats per group).After adaptive feeding,rats in all groups except the sham-operated group were treated with bilateral ovarian castration to establish the PMOP model.Each day,rats in the Qianggu Capsule group received 0.054 g/kg Qianggu Capsule suspension intragastrically,rats in the calcium carbonate group received 1.670 g/kg calcium carbonate suspension intragastrically,and rats in the HGMLP low-dose and high-dose groups received 0.188 g/kg and 0.375 g/kg HGMLP intragastrically.Rats in the sham-operated group and the model group received an equal volume of normal saline intragastrically.After 90 consecutive days,serum estradiol(E2),estrogen receptor α(ERα),procollagen typeⅠN propeptide(PINP),and tartrate-resistant acid phosphatase 5b(TRACP-5b)were detected by ELISA.Total antioxidant capacity(T-AOC),superoxide dismutase(SOD),catalase(CAT),and malondialdehyde(MDA)levels were measured by colorimetry.Bone mineral density(BMD),trabecular number(Tb.N),trabecular separation/spacing(Tb.Sp),trabecular thickness(Tb.Th),and structure model index(SMI)were measured by Micro-CT,and the microstructure of cancellous bone was observed.The expressions of osteoprotegerin(OPG),receptor activator of nuclear factor-κB(RANK),RANK ligand(RANKL),phosphorylation of forkhead box O3(FoxO3α),Wnt2,β-catenin,and peroxisome proliferator-activated receptor γ(PPARγ)in rat femur tissue were detected by Western blotting.Results(i)The serum levels of E2 and ERα increased in the Qianggu Capsule group and HGMLP groups,compared with the model group(all P<0.05).(ii)Compared with the model group,the serum levels of PINP,TRACP-5b decreased and PINP/TRACP-5b increased in both the Qianggu Capsule group and HGMLP high-dose group(all P<0.05).(iii)The activities of T-AOC,AOD,and CAT in the Qianggu Capsule group and HGMLP groups were higher than those in the model group,while the content of MDA lower(all P<0.05).(iv)Compared with the model group,the femoral BMD,Tb.Th,and Tb.N increased in the Qianggu Capsule group and HGMLP groups,while the femoral Tb.Sp and SMI decreased(all P<0.05);the femoral BMD increased and the Tb.Sp decreased in the calcium carbonate group(all P<0.05).(v)The protein expressions of RANKL,RANK,FoxO3α,and PPARγ in the Qianggu Capsule group and HGMLP groups were lower than those in the model group,while the protein expressions of OPG,Wnt2,and β-catenin were higher(all P<0.05).Conclusion HGMLP can significantly increase estrogen levels,inhibit osteoclast differentiation,and inhibit bone resorption in the PMOP rats.It also alleviates oxidative stress,promotes osteogenic differentiation,inhibits lipogenic differentiation,improves bone formation,and recovers the balance between osteoclasts and osteoblasts,thus achieving prevention and treatment of PMOP.The potential mechanism of HGMLP may be related to regulation via the OPG/RANKL/RANK or FoxO3α/Wnt2/β-catenin/PPARγ pathways.